How Marketing Teams Should Optimize Website for Conversions that Align with B2B Sales

You might have heard before that marketing and sales can sometimes experience the business version of a sibling rivalry, but it’s not quite what you think.

Within business-to-business (B2B) organizations, marketing’s focus is on generating leads, while sales focuses on getting those leads to close. A disconnect happens when your marketing team (with good intentions) focuses on volume over quality, therefore resulting in passing over a high volume of leads to sales that just won’t close.

In this article, we’ll walk through a framework for how to categorize leads that come in through your website, how to build website messaging and landing pages that are consistent and relevant for each type of category, and how to optimize for intent as you go.

A General Framework for Categorizing Website Leads

It might seem obvious that your marketing team should focus on quality over quantity, or ideally both at the same time, but in practice the two can get a bit muddled.

We recommend generally categorizing leads into three different buckets:

  • High volume, high intent. These leads should be sent to sales and prioritized.
  • High quality, Low intent. These leads should be sent to a nurture funnel where they continue to be educated and engaged.
  • Low quality. These should get filtered out altogether, or directed to a different offer.

Ultimately, we’re talking about being more efficient with  qualification by allowing your website to do a lot of the work for you.

This includes building consistent messaging for each lead category, building and presenting relevant landing pages for those people, and optimizing for intent as you go.

Create Messaging that’s Consistent and Relevant

In order to qualify each website visitor as a member of one of the lead categories above, you’ll need to be able to automatically consider two things before displaying website content:

  • How that person got to your website. The messaging on the page they visit should be consistent with the email, ad, social posts, blog post content, or search result that preceded it.
  • Their business demographic. Use marketing automation, CRM and / or 3rd party data to ensure that messaging is also relevant to their business size or industry. Focus on the industries and business sizes that have an expected value for your sales teams, and send all others into the low quality bucket.

One effective way to do so is to display case studies from relevant industry competitors, if you have them available. 

For example, if someone from Wells Fargo visits your fintech website, they’ll likely respond more positively to a landing page with logos or success stories from Chase or Bank of America then from Investopedia or Stripe. If that’s not in the cards for you, focus on business size first. Before showing a Wells Fargo visitor logos from a fintech startup, show a success story from Macy’s, Delta, or another enterprise business.

This example from Shopify that’s optimized to attract businesses in e-commerce fashion. The logos and success stories listed on the page include e-commerce fashion brands, like AdoreMe, Cee Cee’s Closet and Coco and Breezy, immediately signaling to other fashion e-commerce companies that Shopify’s solution might be a good fit for them.

This example from Shopify that’s optimized to attract businesses in e-commerce fashion.

FunnelEnvy offers reverse IP, or account matching, and real time data integration to help marketers surface insights that allow them to display industry-specific webpages like these.

We also help companies display pages based on other types of data, like funnel stage, company size, and more.

This example from a large call center showcases how experimenting with personalized offers on their website by buyer segment led to an increase in qualified leads. 

This example from a large call center showcases how experimenting with personalized offers on their website by buyer segment led to an increase in qualified leads.

In fact, MQLs increased by 10X between March and June of 2020.

Graph showing MQLs increased by 10X

Landing pages that set the right expectations

Your landing pages essentially start the sales process by presenting your products to people for the first time. For them to be effective, they need to accomplish two things:

  • Mimic your sales people. This should be true for every lead category. Once a person converts through your website and makes it to the stage where they speak to sales, they shouldn’t receive an entirely different message than what led them to convert in the first place.
  • Clearly communicate what each site visitor should expect next. This will change depending on the lead category. If your site visitor is categorized as “high quality, high intent” and on their way to talking to a sales person, tell them that. If they’re getting redirected to a different offer or getting more information sent to their inbox, tell them that instead. 

One common mistake we see companies make is sending leads to a discovery meeting with a sales development representative (SDR) after they register for a demo. They’re expecting to see the product, when in fact, they end up in a frustrating meeting where they’re asked a lot of questions, afterwards which the real demo is scheduled depending on how they’ve qualified.

One way to rectify this is to make the discovery process part of the inbound flow, like we do at FunnelEnvy.

Our quick questionnaire helps us to categorize site visitors that convert so that we can set expectations for what will happen next, once they’ve completed the form.

Take a moment to fill out this questionnaire

Here’s another example that qualifies leads using company size and sales strategy:

Example that qualifies leads using company size and sales strategy

Optimizing for intent as you go

You’ve created messaging for each lead category and set up your landing pages so that the right expectations are set. Now it’s time to take it a step further by putting in place a mechanism to filter out low-quality leads or show them a different offer.

If a website visitor that’s not a highly valuable lead for your sales team comes along, you’ll want to be able to identify them with data that reveals their business size, industry, title, or any other identifying signal that makes a difference for you.

If someone comes along that doesn’t fall into any of the buckets you’ve identified as high value, consider sending them to your self-service solution (if one exists) or including a message upfront that right now, you’re just not the right fit for one another.

While it might seem scary to direct some leads away from sales, it can actually improve your sales team’s productivity and have a positive impact on revenue.

Working with FunnelEnvy, one startup increased their monthly marketing qualified leads (MQLs) by 30%, and grew revenue from closed or won deals by 250% the following quarter. Here’s what that success looks look over time:

One startup increased their monthly marketing qualified leads (MQLs) by 30%

This success came from optimizing their website to align with their B2B sales strategy, and by only surfacing high quality leads to their sales teams that were ready to buy.

Bonus: treat your high quality leads like gold

Those leads that are high quality and have the appropriate purchase intent should be treated like gold. 

To ensure that your sales team is successful, make sure there’s an established service-level agreement (SLA) on when and how sales is following up on those leads. For example, Marketo’s sales team commits to a 24-hour SLA.

If a tight 24-hour turnaround isn’t in the cards for you, automate your follow-up process with marketing automation or your customer resource management (CRM) software.

End the infamous sibling rivalry

The infamous sibling rivalry amongst marketing and sales isn’t actually a sibling rivalry at all — in fact, it only exists when these teams try to help one another in the wrong way.

Your website can do most of the heavy lifting to close this gap and help to qualify leads that are sent to sales automatically. 

If you’re looking for a custom solution to help personalize your website content for leads of different types, FunnelEnvy can help — contact us.

Solving the Revenue Funnel Data Challenge


Transcript:

Hi, everyone. I’m Arun from FunnelEnvy. Today I want to spend some time talking about how we solve the revenue funnel data challenge.

Of course, many of you are running multiple campaigns on lots of different channels. You have digital advertising, paid acquisition campaigns that are heavily optimized, and you spent a lot of time getting people into your marketing automation platform and running really personalized email nurture campaigns to them.

Now, of course, the main problem that we focus on at FunnelEnvy is that the main thing in the middle that glues a lot of that customer journey together is your website. Of course, for many of us, it’s a static experience. Unlike the other channels, prospects and customers keep coming back to that same static website. In many cases, it’s just not keeping up and dragging down your conversion rates and ultimately your pipeline that you’re delivering to the sales team.

Now, that’s a broad example of some very specific demand gen website problems that we commonly run into. You’re probably looking at website analytics, and if you’ve spent any time in there, it’s not easy to tell which experiences and offers, things like landing pages or other offers, content, are actually contributing to revenue. Maybe you’re running experiments and campaigns on your website, and it’s also hard to measure the pipeline and revenue impact from those website experiments. Of course, a static website that’s showing the same thing to every buyer at every stage isn’t very effective at moving prospects efficiently through the funnel.

Now, of course, the demand gen revenue journey is long and complex. This is just one example of someone coming to the site, downloading content, getting on an email sequence, attending a webinar, talking to sales who finally opens it up and later on closes the deal. The important thing to understand is that, of course, that revenue journey occurs in multiple different contexts, multiple different channels, and ultimately different platforms in our backend martech stack, from the website and the website analytics to the marketing automation platform and ultimately the sales team and the CRM platform.

Now, the net effect of this is we end up creating a lot of data silos in our stack. Website analytics, the CMS or the optimization tools, maybe third-party firmographic data providers, our backend systems like marketing automation and CRM, these are all silos of information that all have individual pieces of that entire customer journey. We can think of those individual pieces as pieces of the puzzle that, if we put together, can actually present a cohesive picture of those individuals and accounts and their opportunities as they move throughout that customer journey.

Now, the important thing is having that glue that can bring all of those puzzle pieces together and not only receive data from those individual systems, but also feed them and also feed our business intelligence or reporting. For now, we’re going to call that a customer data platform, or CDP. This is similar to a data warehouse, but it has some very specific features that we want to see to be able to solve some of those problems that we were talking about.

First off, it’s not just sufficient for this CDP to receive data. It needs to have bi-directional integration to a lot of these solutions so it can pass data between these different platforms. Certainly, it unifies all of these puzzle pieces, or that profile data, and because we’re talking about demand gen, it happens both at an individual and an account level. It has that full view of the customer journey, so unlike website analytics that’s only looking at what’s happening on site, it has that perspective tied to that unified customer profile of what happens not only on the website, but also down the funnel as that leads to account progress towards revenue. It allows for rich segmentation because we have those unified customer profiles and full perspective on that buyer journey, and because we’re talking about website optimization, allows for real-time resolution to be able to target those different audiences on the website.

Let’s get into some of the specific use cases of the customer data platform. First off, we can use it to enhance our existing web analytics. If you spend a lot of time looking at your website performance and in platforms like Google Analytics you know that you’re typically only looking at those vanity metrics, things like bounce rates and visits and exit rates. Unfortunately, a lot of the interesting data that we have lives in our marketing automation, our CRM, the leads, contacts, accounts, and opportunities that we’re really seeking to improve and understand.

By pumping this data into our CDP and unifying it and then feeding those down-funnel outcomes into our web analytics, as well as our reporting and dashboards, we get a much more complete picture of that revenue journey for that visitor. This lets us answer questions like which experiences and offers on my site are actually contributing to revenue, and how much? You see here a landing page report, but instead of only looking at your typical vanity metrics you see on the right, we actually can visualize the closed one revenue of each of those landing pages. Of course, you can take any of those dimensions that you’re typically looking at in a web analytics and understand the pipeline and revenue impact this way.

You can also answer ad hoc questions through dashboards, like my website traffic, not just in terms of numbers, but by different buyer stages and the expected revenue of each. This often starts the hypothesis process of how can I actually target those different buyer stages differently to accelerate them through that revenue funnel.

Once you actually get into running experiments and campaigns, it can be very difficult to understand how much pipeline and revenue those experiments and campaigns are actually generating, especially if you’re using a multi-touch attribution model, which many of you are. We can solve that problem by bringing, again, that lead, contact, account, and opportunity data, as well as the touchpoints in my attribution model and the test and campaigns from the optimization platform, and feeding those into my reporting and business intelligence environment.

By doing that, we can start looking at the amount of sourced pipeline using that attribution model that my website campaigns and experiments have delivered over time. We can start comparing campaigns, not just on their ability to get people to fill out a form, but based on the actual pipeline and revenue impact that they’ve had. We can look at individual campaigns and the variations in those campaigns and understand which variation is most effective, again, not just in terms of those onsite vanity metrics, but their ability to deliver results down the funnel.

Finally, when we’re talking about optimizing the revenue funnel, a lot of it is about targeting in real time and targeting the right offers to different personas, different groups of accounts, and my personal favorite, by buyer stage, to move prospects more efficiently through the funnel. Now, to do this, again, we’re bringing over that same marketing automation and CRM data, but potentially also that website behavior from web analytics, and in this case, feeding that into audiences in our content management system or our testing and optimization platform. In this case, this isn’t a reporting use case, so that audience has to be delivered in real time based on an individual visitor as they come into the site. If you can do that though, we can start doing things like personalizing those offers based on that buyer stage and where they are in the journey, or even differentiating offers and changing the experience in real time to present the best offer based on the persona that’s coming to the site.

With that, I want to leave you with some takeaways. If you’re a demand gen marketer and you’re looking at your website performance and even optimization of it, our recommendation is always not to settle for top-of-the-funnel KPIs. Those vanity metrics, those engagement metrics, even form conversions, they’re not sufficient. Really, you should be trying to align your efforts with the way the rest of the team and organization measure success. For a demand gen team, that’s based on pipeline and revenue impact.

Of course, demand gen sites, demand gen marketers, typically deal with long customer journeys. What that often means for your site is that you have a lot of return visitors. They’re coming back to the site at different stages in the buying journey with differentiated intent, but the measurement of pipeline and revenue and the ability to understand those different buyer stages and ultimately target them is really related to how efficiently you can bring that data together and activate it in real time.

Then finally, many of you may have already invested in a data lake or data warehouse to unify that data that you have in these different silos together. Typically, this is done for attribution use cases and other reporting and measurement use cases. It’s a great starting point. Our CDP often compliments existing data lakes or data warehouses, but the reason that we have to compliment it is that typically those are solutions that aren’t built for that real-time use case. If you get into the targeting and activation of that data in the milliseconds that are required by the time a visitor comes to the site and you deliver them that web experience, it requires a real-time source, in our case, the FunnelEnvy customer data platform.

With that, I want to thank you for listening today. Bye.

 

The Secret to Making Your ABM Personalization Campaign a Success

For all the demand generation leaders out there, I’ll bet you’ve engrossed your partners, sales directors and higher level leadership team on the subject of account based marketing personalization. But be honest, do you really know what a successful outcome looks like?

visual screenshots of abm personalized accounts

ABM-based personalized campaigns are the targeted, personalized experiences that either speak one-to-one to an account, or to a group of important accounts. Per a definition found online,

“Personalized campaigns that are designed to engage each account based on the marketing message on the specific attributes and needs of that account.”

In following this logic, you’ve decided that certain accounts are more important than others, and therefore are worth the effort of this level of personalization. Great! Typically, demand generation marketers follow these steps:

  1. Identify targeted accounts
  2. Target those accounts in real time with personalized campaigns
  3. Measure the effects of those campaigns

Steps one and two are pretty straightforward, and certainly there are potential pitfalls, but step number three is critical. The truth is the wrong measurement strategy could doom your ABM personalization efforts to failure.

pyramid-three-steps-abm-personalization

Choosing the Right ABM Measurement Strategy

A common way to evaluate the effect of an onsite experience is through an A/B test. This is the traditional conversion rate optimization (CRO) approach. You might run a randomized A/B test, evaluate the effect of personalizing your homepage against a baseline or control, and measure an on-site goal, like lead conversions. You can carry out this type of testing in a variety of platforms, measure the effect on your goals, and try to determine the overall impact on your personalization efforts. 

homepage-optimizely-cro-website-optimization

It’s important to note however, that this approach makes several assumptions. First, it requires a large sample size to establish confidence based on statistical significance. It also assumes that all of these conversions are the same.

If you’re only looking at the difference between lead conversion for the baseline and lead conversion for the personalized option, then you’re assuming the conversions carry the same weight, measuring impact based on the quantity of those conversions, but not necessarily the qualityWe should ask ourselves, are these assumptions consistent and compatible with our ABM strategy?

When we think about ABM, the fundamental goal is to capture more revenue from a smaller number of accounts. That’s how you can justify the investment in targeted ads, website personalization, or direct mail.

graphs-target-image

Keep in mind that the further up the ABM pyramid you climb, the smaller the number of accounts that can potentially drive value or expected revenue. In many cases, those white glove accounts could be worth a hundred times more value than an SMB account. Since those accounts are likely larger enterprises, they’re also likely to take longer to close.

What to Include when Measuring your ABM Personalization Campaign

Your ABM personalization strategy should include a quality metric, which includes pipeline and revenue, considered over a longer period of time.

Now this can conflict with the CRO approach that we mentioned earlier. This approach, however is very transactional, top-of-funnel, and assumes that each conversion is the same.

You may consider or are actively engaging in the traditional CRO approach to pass variation information back from your optimization platform to CRM for analysis against pipeline and revenue. Often times, this means embedding those variations that users saw in a hidden field on a lead capture form, and then building a custom report in your CRM data on the backend.

 simple attribution solution

Will this get you better insight into the down-funnel impact from your personalization experiences, like pipeline and revenue? It may, but you could also wind up with a one-off solution for the website experience that doesn’t align with the way the rest of your demand gen team measures and attributes revenue.

The Right Attribution Model for ABM Personalization

You may be running a multi-touch attribution model, either with an off-the-shelf tool like Visible, or a custom solution.

These work well for longer journeys by allocating revenue back to customer journey touchpoints, like the first touch, lead creation or opportunity created, granting credit to the triggers that influenced the conversion.

bizible full attribution model path

Image Source: What is a “Full Path” Marketing Attribution Model? (Bizible | Link)

B2B attribution solutions are inherently account-based and they’re typically used for channel and campaign analysis, but they can also be used to measure the effect of on-site activities like ABM personalization campaigns.

Now, the real advantage here is by integrating your website experiences with your multi-touch attribution model. You’re aligning your website activities to the measurement strategy used by the broader demand generation team. So how does this work?

Let’s say you have touchpoints established, and you’re allocating revenue in some proportion across each one. Here, the actual percentages don’t actually matter as long as you’re are allocating revenue back to new customer touchpoints.

abm personalization touch points

Once you know the revenue at a certain touch point over a period of time, with attribution, you’ll be able to assign credit back to the activities that influenced that touchpoint conversion. As I mentioned earlier, it’s typically done at a channel and ad campaign-level, but there’s no reason that an onsite experience can’t be an influence over a touchpoint as well.

Campaigns and variations are a couple of example of onsite influences, but you could also consider chatbots, content, and anything that influenced a touchpoint. Eventually, you’ll see pipeline and revenue credit associated with the influencing on-site experiences of those touch points. 

The Better the ABM Attribution, the Better Your Metrics

Rather than report on percentages like conversion lift on a superficial vanity metric, you can report on campaigns over time with respect to their sourced pipeline. These insights grant you a better understanding of the impact your on-site campaigns have on your business.

graph of results over time

Additionally, you’ll see the impact your campaigns have not only in terms of onsite metrics, but based on sourced, influenced pipeline and revenue, and closed deals. 

personalization by intent chart

Variations within your experiments will give you the view you need to report on uplift based on whether pipeline or revenue correlated directly with your attribution model.

testing variation chart funnelenvy

Let’s talk about other ways you can ensure your ABM personalization efforts are a success. Start your revenue insights journey by measuring your revenue contribution of existing offers. By aligning this with your attribution strategy, you’ll gain deeper insight into your on-site offers and assess their revenue contributions.

Don’t Forget About Segmentation

Segmentation is a big part of account-based personalization. The audiences that you create will have differentiated intent. You wouldn’t want to spend time creating audience segments that are effectively the same and trigger the same experiences.

Think about how your account clusters and account groups are differentiated, and what offers they’re going to want to see that are specific to their interests within their own groups of accounts. 

Now let’s pivot to the must-avoids. This includes what we call “vanity personalization,” where you add the name of a customer or account coming to the site. Instead, focus on the offers you’re putting in front of your visitor.

The ideal is to present a more relevant offer throughout the demand generation funnel to your visitor. When segmenting, think about the offers presented to these target accounts, and focus on how to increase their relevancy.

Remember, this isn’t just a top-of-funnel activity. Obviously we’re talking about demand gen marketing in this post, but consider your full customer journey as a long revenue funnel.

Once you enable yourself with the capability to personalize your ABM campaigns, think how your business can better align offer and optimize, not only for your top-of-funnel, but for each stage of your buyer journey. 

Optimize your Revenue Funnel by Focusing on the Offers

Let’s take a step inside the data-driven demand generation marketing team. The biggest concerns on the CMOs radar are that the acquisition costs are too high and not hitting their pipeline or revenue goals.  Now looking at the data, we know that not only are they spending a lot on paid and organic traffic, but the quality of the traffic is good, and it’s not converting.

So, of course, the next question would be – what can they do about it? A common answer is to focus on website conversion rate optimization, which involves running online experiments. That’s something you can put a budget around and prioritize but recognize that your executives are going to want to see impact based on pipeline and revenue and probably want to see it fast.

Online Experimentation

Back in 2017, the Harvard business review published an important article digging into the power of online experimentation. In it, they correlated successful business outcomes to a culture of experimentation. 

harvard business review article title

Image Source: The Surprising Power of Online Experiments (Harvard Business Review | Link)

The article cited examples like the one below from Bing,  who tested multiple different colors on their site, ran experiments. and realized an incremental $10 million in annual revenue from these experiments. 

small changes with huge image image harvard business review article

Image Source: The Surprising Power of Online Experiments (Harvard Business Review | Link)

Similarly, Google ran a test with 40 different shades of blue on their site. When they ran those experiments, they achieved $200 million in incremental revenue. Given these results, should we, as demand gen marketers, be running the same experiments?

In our opinion and experience, no, you should not.

You’re not Google or Bing. Leaving aside traffic considerations, you’re trying to influence B2B buyer behavior over customer journeys. And the reality is that groups of buyers that consider enterprise solutions are not going to buy based on the button color or other small cosmetic changes.

This is important because experimentation comes with a cost. Not only do you have people and the technology costs of running online experiments, but also your organizational ability to make decisions. So, focus on the elements that would deliver revenue and influence those B2B buyers when you’re thinking about experimentation.

When we think about the B2B buying journey or the revenue funnel it’s common to conceptualize it as a series of buyer stages. As prospects progress through those stages, they do so through exchanges, in which you’re offering something to that prospect in exchange for something else. The offer could be some content in exchange for their attention, an event, or an opportunity to speak to the sales team in exchange for their contact information. Ultimately those offers are how they learn more about your solution and how it would benefit them. 

funnelenvy funnel image

From our experience and the testing that we’ve done, the highest leverage use of experimentation for the demand gen org is to improve the relevance of those offers and the ease of engaging with them throughout the buying journey. Of course, we always want to ensure we measure the impact of those experiments based on the KPIs that matter – pipeline and revenue.

Optimizing Offers

logistics transportation image of form

What does it mean to optimize offers? There are three components to an effective offer. One, of course, is the offer itself. That item you’re proposing to exchange with that visitor or prospect for them to understand your solution. The more relevant it is, the more effective your ability to convert them will be.

The second important aspect is how you frame it. Our primary focus here is the headline and Call to Action (CTA). Your headline is important because a visitor will spend five or ten seconds deciding if they want to stay on your site or hit the back button and go somewhere else. So, entice them to continue reading the content on the page.

Finally, the third element of the offer is the exchange and how they provide what you want. Most likely on your site this is a web form, but it doesn’t need to be. It’s increasingly common to see conversational marketing tools (chatbots) that accomplish the same thing by providing that medium of exchange for the offer.

Examples

Let’s look at some examples of how you could optimize your offers.

Landing pages are a great starting point for thinking about your offers. Many of you are probably running traffic to dedicated landing pages and putting an offer in front of the visitors hitting it. But not every visitor is interested in the same offer. In the example below, we recognized when working with a customer that they had three viable offers for those visitors coming through their paid campaigns. And rather than only showing them one, we use data to dynamically personalize the offer itself as well as framing and the page layout to reflect what might be most relevant to that visitor.

landing page offers comparison

When we ran the experiment against the static landing page we saw a 44% improvement in revenue per visitor. 

For most of us the most trafficked page on our site is the homepage. And on your homepage the “above the fold” section at the top gets most of the attention. Many of us think about our homepage in the context of welcoming the first time visitor and introducing your solution as in the example below.

fitch-solutions-landing-page

For SaaS and Demand Generation websites it’s common to have a lot of returning traffic. Since return visitors are familiar with your solution, it wouldn’t make sense to show them that same offer. In an experiment, we targeted these return visitors and the solutions they showed interest in and presented them on the homepage. In this case, those offers were buried in the site and require additional navigation. By presenting this offer they would likely be interested in and serving those directly on the homepage, we saw almost 55% improvement in conversions coming through this page.

fitch-solutions-home-page-offers

You can also target well-defined buyer stages. In the following example, we have a customer with a freemium model where visitors on the free plan come to the homepage and see a CTA or a button prompting them to “Upgrade Your Plan”. The baseline experience was to take them to a set of SaaS plan tiers where they could select the one that they would upgrade to. 

pricing-table-personalization-offer

Using this data, we can identify the specific plans most relevant for any individual and offer them directly on the homepage. The framing included the benefits and replaced the CTA with the cost of that specific plan we recommend. Since we recommend a single upgrade plan, we bypassed the plan selection (and the friction it created) and took them directly to the credit card to upgrade. By removing friction and presenting them with a more relevant offer, we saw an almost 70% improvement in revenue per visitor coming through this experience.

buyer-stage-changes-to-website

The most common mechanism of exchange for the offer is the web form, and as a result, we spent a lot of time optimizing them. It’s important to recognize that there’s a lot of friction for the visitor when they encounter one of these forms.Even if they’re interested in the offer, they face the prospect of handing over their email and other personal information, which often presents a big hurdle. Since it’s common to see drop-offs at this stage, we would like to take those contact forms and reinforce the benefit and the value to the visitor filling them out. In the following example, we tested an updated version of the form page resulting in an 85% improvement in conversions.

form-optimization

If you have the data, you can get sophisticated with offer personalization. It’s common to see pages like the one below. It is a product page that contains multiple offers for different personas within the organization. Unfortunately, when you try to put them all on a single page, they compete for attention and blend in, making it hard for users to know which one is relevant for them. 

TIBCO-homepage-before-personalization

In this case, we target specific personas visiting the page based on data we had in the marketing automation platform and identify the most relevant offer. By testing variations that replace the default experience with a single focused offer, we see an almost 50% improvement in revenue per visitor.

TIBCO-homepage-after-personalization

Final Thoughts

It’s possible to waste time, effort, and money optimizing inconsequential elements of your website. For demand generation marketers, the highest leverage things to focus on are the offers – specifically their relevance to the visitor and the ease of engaging with them.

Before you undertake this experimentation it’s important to make sure you have solid revenue insights. What that means is, evaluating your existing offers as well as future experiments based on their pipeline and revenue contribution.

Some of the personalized examples above require some segmentation. Our recommendation is to prioritize segmentation based on the differentiated intent and addressable size of those segments. We often find that marketers are running building audiences that can only address 5-10% of their audience, or ones that don’t have meaningfully different intent from one another. Ultimately those aren’t going to have much value when it comes to optimizing offers.

This is why we start with buyer stages as our starting point for segmentation because it a large set of well-understood segments with differentiated intent – buyers at different stages will naturally gravitate towards different offers. The vast majority of the visitors coming to a demand gen site fit into anonymous, known lead, active opportunity or existing customer.

Finally, when it comes to improving offers, start with common sense ideas. If you start thinking about your buyer stages, some opportunities should become apparent. For example, should a known lead see a lead capture form, or can we repurpose those pixels for something more relevant? Similarly, should existing customers see the “Request a Demo” or “Talk to Sales” CTA? Maybe there’s an opportunity to get them to support resources or event upsell them. 

What’s stopping you from generating more revenue by improving offers on your website? If you’re a Demand Gen marketer and need help, feel free to get in touch.

We Know Why Your Online Ads Aren’t Scaling Revenue (And How to Fix It)

When you put too much pressure on something, it cracks. 

Online advertising is no exception. The cracks in this ecosystem have turned into gaping holes, and those holes are why your paid ads aren’t scaling.

Three of the big ones are often in the headlines: the death of the third-party cookie, attribution as an almost impossible feat, and data privacy which is getting clearer, but still murky at best.

Yet, most of us put up with it. 84% of B2B marketers use paid distribution channels (read: Instagram, LinkedIn, Facebook, YouTube, etc.), which would be one thing if the value of those channels was clear, but a staggering 47% of us admit that we can’t measure ROI and 18% aren’t sure if they can or not.

Despite these shortcomings, when we need to scale, our first thought is often growing the budget for online ads, but will that really move the needle?

In this article, we’ll break down why your ads aren’t scaling revenue by analyzing their actual contribution to your sales funnel, calculating what would really happen if you had your dream budget, and how to fix the gaping hole in your funnel that paid channels leave unfulfilled.

What do Paid Ads Actually Contribute?

Pretty much everyone buys ads from Facebook and Google, but it’s also quite common for B2B marketers to buy ads from LinkedIn. The rest of the web is fragmented and even harder to navigate than these channels, so for the sake of argument, let’s focus on those three.

  • Search ads are effective, but have incredibly narrow margins, and quickly get costly if you’re not paying attention.
  • Facebook ads have better margins, but only if you can keep up with inevitable creative fatigue on behalf of your audience.
  • LinkedIn ads have the best margins of all, but they’re incredibly expensive, with an average cost of $5.26 a click versus Facebook’s $1.72.

So, they do work, but the margins are small and the cost is high. Because of this reality, most marketers make incremental investments focused on driving traffic to web pages.

We took a look at website traffic from two of our high-growth clients, and saw that those expensive investments were a drop in the bucket in comparison with organic channels. 

Direct and organic traffic made up 70% to 75% of all traffic, whereas traffic from a whopping five to six paid channels only made up 25% to 35%.

In these two examples, paid search specifically accounted for 13% and 9% respectively.

paid traffic example case study funnel envy 1 paid traffic example case study funnel envy 2

But what if that 13% of traffic is where all of the revenue came from? Even in that unlikely scenario, we can’t expect it to continue to grow if this marketing team tried to scale their paid search buys.

This analysis from Search Engine Land shows that on average, after hitting a certain inflection point, your margins get smaller and smaller. This is true for all marketing channels, and is also known as The Law of Shitty ClickThroughs.

paid search roi return on investment search engine land analysis

Image Source: Paid Search Portfolios: The Good, The Bad & The Ugly (Search Engine Land | Link)

This is not to say that paid advertisements don’t have a place in your marketing mix, but that alone, they won’t scale revenue profitable or quickly. 

Optimizing the entire journey, which requires analyzing all channels as a whole, is the only way to scale revenue optimally. And since website traffic comes from all channels and your website is where buyers at every stage of the funnel engage, you can only do that if your web analytics are measuring revenue instead of top of the funnel vanity metrics.

How do You Scale Website Traffic so that it Ends in Revenue?

Instead of narrowly focusing on incrementally increasing website traffic with paid ads, the answer to revenue at scale lies with focusing on improving website conversions across all channels and at every stage of the buyer journey.

The chart below is a snapshot traffic analysis spanning one quarter, from a FunnelEnvy customer. This B2B SaaS company currently sees a 5% conversion rate from paid channels, which is higher than their direct and organic channels — at 2.5% and 3% respectively.

It might therefore seem logical to focus on scaling their paid channels. Let’s see what happens when they give it a shot.

This B2B SaaS company’s marketing team tested spending 50% more on paid advertising one quarter, resulting in an additional 1,000 leads. When they instead focused on optimizing their website funnel across all channels, they saw an additional 1,755 leads, a 10% improvement over just scaling paid ads alone.

web funnel lead optimization funnel envy example paid ads not scaling

As we’ve seen, online ads are subject to the same laws of diminishing returns as any other channel. So, actually achieving 10% growth from your website (which accrues to all acquisition channels), is likely to be much easier than generating 50% or more growth from your paid channels.

Optimizing your website doesn’t have to be an exclusively lead generation focused activity. In fact, you’re likely to get much better results if you can optimize all the way down funnel to pipeline and revenue. To illustrate the impact, let’s compare what happens when you optimize your top of funnel (TOFU) conversion rate with bottom of the funnel (BOFU) metrics like opportunities and closed deals.

The following FunnelEnvy customer is a B2B SaaS company in the fintech space, looking to increase the number of closed deals per quarter and reduce their customer acquisition cost (CAC).

They average about 600,000 visits per quarter and spent about $450,000 across all paid channels. When they increased their lead generation focused conversion rate alone by 30%, they saw a corresponding increase in deals closed, and a 23% reduction in CAC. However when they extended conversion improvements all the way down the funnel they saw an even greater increase in closed deals (50%), and a larger (33%) reduction in CAC.

This “Revenue Funnel Optimization” requires you to identify visitors at different buying stages on your website, and to target them with more relevant offers and experiences. 

This table captures the impact of optimizing through various stages of the funnel — leads (TOFU), pipeline (opportunity creation) and closed or won deals (revenue):

web funnel funnel envy example paid ads not scaling TOFU BOFU

An Easier, More Scalable Path to Growth Exists Across All Channels, Not with Paid Ads

The bottom line — simply increasing your spend on paid channels is not the answer to scale, and there’s a lot more growth to be found if you take into consideration how other channels impact your funnel.

As the paid advertising ecosystem racks up more and more problems and gets increasingly expensive, this is a great time to focus on elevating the value from other channels that impact your funnel.

If you’re not quite sure where to start, you’re not alone. 68% of B2B companies haven’t even identified their sales funnel. FunnelEnvy’s solution helps you close the gap between website analytics and revenue and target buyers at each stage of their journey.

If you’re a demand gen marketer that needs to scale growth efficiently learn more about our solution for Revenue Funnel Optimization.

Revenue Funnel Optimization Focus on the Offers

Transcript

Hi, everyone, I’m Arun from Funnel Envy.

We help demand gen marketers increase pipeline and revenue through revenue funnel optimization.

And today I want to talk about why you should really focus on the offers. I’ll explain what that means as we go through this.

Now, let’s take a step inside the data driven demand generation marketing team, maybe the top problem on the CMOS radar is that the acquisition costs are too high and they’re not going to hit their pipeline or revenue goals. And so she’s asking that the head of demand gen, you know, where’s the problem?

Now, looking at the data, being a good data driven marketer he comes back with, you know, they’re spending a lot of money on unpaid and organic traffic. The quality of that traffic is good, but it’s just not converting like it should be.

So, of course, the natural question is, what can we do about it?

Now very good answer and a common answer is to focus on website conversion rate optimization. And that typically involves running a lot of online experiments.

So you can budget that, make it a priority but recognize that those executives are probably going to want to see impact based on pipeline and revenue and probably want to see it fast.

So let’s dig into online experimentation, back in twenty seventeen the Harvard Business Review published this important study and article really talking about the power of online experimentation and correlating successful business outcomes to a culture of experimentation. They cited examples like this from Bing where bing tested multiple different colors on their site, ran experiments and realized an incremental 10 million dollars in annual revenue from these experiments.

Similarly, Google ran a test with 40 different shades of blue on their site, when they ran those experiments, they saw 200 million in incremental revenue. And given these results, should we as demand gen marketers be running the same kind of experiments?

Well, in our opinion and in our experience, no. You’re not Google or Bing, leaving aside traffic considerations, you’re trying to influence B2B buyer behavior over a long customer journey. And the reality is that groups of buyers that are considering enterprise solutions are not going to be influenced to buy based on the button color or other small cosmetic changes. And this is really important because, of course, experimentation comes with a cost. Not only do you have the people and the technology costs of running online experiments, it’s also an impact on your ability to make decisions as an organization. So, it’s really important that when you’re doing this, you focus on the elements that are actually going to deliver revenue and influence those B2B buyers.

Now, when we think about the B2B buying journey or the revenue funnel, you can think about it as various stages and as prospects progress through those stages, they do so through a series of exchanges. This is fundamentally the heart of marketing where you are offering something to that prospect in exchange for something else that could be a piece of content in exchange for their attention or their contact information, that could be an offer to attend an event, that could be an offer to talk to the sales team, it’s some offer through which they learn more about how your solution is going to benefit them.

So from our experience and in all of the testing that we’ve done, the highest value, the highest leverage use of experimentation for the demand gen org is to improve the relevance of those offers through that revenue funnel, through that buying journey and the ease of engaging with it. And of course, we always want to make sure we’re measuring the impact of those experiments based on the KPIs that matter, pipeline and revenue.

So what does it mean to be optimizing offers? Well, we like to focus on three main aspects.

One, of course, is the offer itself, that thing that you’re proposing to exchange with that visitor or prospect for them to better understand your solution. The more relevant it is to that visitor and their intent, the more effective your ability to convert them will be.

The other important aspect of the offer is the framing of the offer, and here we’re really talking about the headlines and CTA’s headline is really important because typically a visitor is going to spend five or 10 seconds, at the most, deciding if they want to stay on your site or hit the back button and go somewhere else. So the more effectively you can position that headline and entice them to continue reading and engaging with it, the more effective you’re going to be.

Third element of the offer is the mechanism of exchange, how they actually exchange what you want from them in exchange for the offer that you are putting in front of them. Typically, this is in the form of a web form, but it doesn’t have to be. We’re also seeing more chat bots, conversational marketing tools that accomplish the same thing, provide that medium of exchange for the offer.

So let’s look at some examples.

Landing pages are a great starting point. Many of you are probably running traffic to landing pages and putting an offer in front of those visitors hitting it. Now, in this case, we recognize working with a customer that they actually had three viable offers for those visitors coming through their paid campaigns to their landing pages. And rather than only showing them one, we use data to dynamically personalize the offer itself, but also the framing and the page layout to reflect what might be most relevant to that visitor. And doing this, we see an almost 44 percent improvement in revenue per visitor when we ran this experiment.

We spend a lot of time working on the home page and specifically that above the fold section of the homepage, at the top of the page where most of the eyeballs go. Now, many of you might have a site and a home page that kind of looks like the baseline experience here where you’re trying to introduce your solution at the very highest level to that first time visitor. But of course, you probably have a lot of return visitors, especially if you’re a SAAS solution, a lot of return visitors who are already familiar with your solution or your offering. And it probably doesn’t make sense to show them that same welcome offer. And in this case, we actually were able to identify visitors and the specific solutions that they were interested in and present that offer right on the home page that otherwise would have been further down in the in the website that they would have had to navigate to. So I presented them with an offer that they were more interested in and serving those as variations right on the homepage, we see an almost 50 five percent improvement in conversions coming through this page.

Now, you can do this based on buyer stage as well, in this example, we have a customer with a freemium model where visitors who are on the free plan come to the home page and see a call to action or a button that says upgrade your plan. When they click on it, the baseline experience was to take them to standard SAAS Plan tiers and they could select the one that they would upgrade to.

Now, using data, what we were able to do is identify the plan, which was most relevant for any individual visitor, and show them instead of a plan selection, show them the specific plan that they should upgrade to right on that home page, as well as the benefits they would get out of that plan. CTA was changed to from upgrade your plan to upgrade to a specific plan at a specific price point. And in doing this, we’re able to bypass the plan selection, kind of choose your own adventure experience and take them directly to the credit card entry and upgrade.

So by removing friction, presenting them with a more relevant offer, we’re able to see and almost 70 percent improvement in revenue per visitor coming through this experience.

Of course, that mechanism of exchange is often the form, and so we spend a lot of time optimizing forms. Now recognize there’s often a lot of friction on behalf of the visitor when they see a form and they start to enter personal information, even if they’re interested in the offer. The act of giving someone your email and other personal information often presents a big hurdle. And this is where you see a lot of drop off in terms of conversion. So one of the things that we like to do is take those contact forms and reinforce the benefit and the value to the visitor of filling out that form.

So you can see an example of that where we take a default contact form, which is kind of generic and make it very focused on the benefits and ran this experiment. Here we see about an 85 percent improvement in conversions coming through this form.

Final example, you know, if you have the data, you can get pretty sophisticated with this. Many times we see experiences like the baseline product homepage that you see here where it’s a solution that actually speaks to multiple personas within the organization. And your team actually has different offers for each of those personas.

Now, when you try to put it on a single page, they all compete for attention and kind of blend in and none of them gets the conversions or attention that they deserve. By using data, we were able to identify the offer that was most relevant to the specific visitor or persona coming to this page and replace that experience with multiple calls to action with a single focused offer that was most relevant to that persona, in this case, a developer or an analyst or a manager. Here running this experiment with those variations we see in almost 50 percent improvement in revenue per visitor.

So the offers are really important to focus on as the highest leverage area of experimentation for the Demand gen marketer on your site.

And I want to wrap up with some final points.

It’s really important before you undertake this kind of experimentation to make sure you have solid revenue insights. What that means is make sure you’re able to evaluate your existing offers based on their pipeline and revenue contribution and that you’re set up to measure your experiment not just based on onsite conversion, but based on their impact to pipeline and revenue.

You saw some examples of segmentation that I walked through and personalization.

Our recommendation is to prioritize your segmentation based on how the differentiation of intent across those segments and the size of your addressable audience. We often find that people are running segmentation only for like five or 10 percent of their audience. That’s not going to be as effective as if you can address 90, 95 percent of the visitors coming to your site. This is why we start with buyer stages as our starting point for segmentation, because it presents both great opportunities for differentiated Intent buyers at different stages, want to see different content and engage in different ways. And it maximizes your addressable audience. The vast majority of the visitors coming to your site fit into anonymous, known lead, active opportunity or customer.

Finally, there are a lot of common sense opportunities if you start thinking about buying stages for more relevant offers and some obvious gaps that you should be able to identify.

Start by asking yourself some simple questions.

Should a known lead see a lead capture form? Does that make any sense or can we repurpose those pixels and that experience for something that’s more relevant?

Similarly, should an existing customer see the requested demo call to action or talk to sales? Maybe not. Maybe there’s an opportunity to up sell them or, you know, get them to support or other resources that may be more relevant.

And with that, I want to thank you for listening today, bye.

Online Ads May Not Be the Most Efficient Way to Grow Your Demand Gen Funnel

Transcript 

Hi, everyone, I’m Arun, the founder of FunnelEnvy.

We help demand gen marketers increase pipeline and revenue through revenue funnel optimization

And today I want to spend a little bit time talking about why online ads might not be the most efficient way to grow your demand and a revenue funnel.

So this came about because I’ve been reading more in a lot of popular blogs, including Rand Fishkin, about something being wrong or, as he put it, rotten in the world of online advertising.

Now, in the article, he cites some pretty eye opening results from prominent brands like Chase and Uber, shedding a light on millions of dollars in an Uber’s case, about one hundred and fifty million dollars of wasted ad spend.

Now, if you bring a little bit closer to home, we work with a lot of B2B in demand gen marketers. This study suggests that about 75 percent of the advertising that B2B brands are doing are failing to produce long term growth.

So that seems like a problem. What do we do about it?

Well, let’s take a step back.

Let’s assume you’re a growth stage B2B demand gen organization, and you need to grow a pipeline by 30 percent and you need to do it fast in the next quarter or so.

Where do you invest your dollars? What do you spend on?

Well, of course, you’ve got the paid channels.

This is an obvious candidate, and the reason everyone loves them is because they’re very fast to add. But of course, the flip side of that is not only are they expensive, they’re also arguably much less efficient.

We’ll talk about why.

On the other hand, you’ve got your own channels, email, and organic search and social, these are cost effective in the long term, but of course, they’re harder and slower to scale.

Now, the one overlooked element in all of this is often the website, and the reason that it’s important is because all of these channels paid and owned funnel traffic to it. So it can be very efficient to scale, but it’s often the least optimized area. Everyone typically deals with static websites and it’s harder for organizations to execute on.

But let’s look at the impact of optimizing that web funnel.

Some data points, first off, when we look across our typical high growth customers, we usually see about 70 to 75 percent of the traffic coming to the site from direct and organic sources. And the remainder, about twenty five or thirty percent split across, you know, a handful of paid channels.

What that practically means is that if you’re trying to grow exclusively through a paid approach, you’re focusing on a single paid channel, you’re optimizing maybe 10 to 15 percent of your traffic. That makes it really hard to grow and optimize your entire funnel if you’re only dealing such a small subset of your traffic.

And of course, many of you know that at some point you start getting diminishing or negative marginal returns on that spend. A lot of the low hanging fruit, it gets carved away and you have to spend more on keywords and ad placements.

So it is possible to optimize your website funnel and grow with scale and speed.

Let’s look at a typical channel distribution in terms of traffic and conversion rates for our customers. And when we look at typical conversion rates across these channels, you get a sense of the lead volume per channel. If we were to spend our efforts growing exclusively through paid and achieve 50 percent growth through the paid channel that would be a good result. And of course, you see here that we’re getting, in this case, about a thousand more leads over the same time period.

But what Web funnel optimization allows you to do is actually distribute that growth across all of your channels. So let’s say you only produce 10 percent growth, but it’s spread across all of these different channels. You’re actually seeing a net increase above the paid channel strategy because you’re able to optimize all of your funnels.

So the point here is that improving that website funnel improves all channels and that can present a much easier path to growth.

Now, too often in the demand gen world and we think about optimizing the website, we only think about it as a top of the funnel activity.

Let’s look at what happens when you go further down funnel. Again here, we’re taking typical industry standard conversion rates through the entire funnel from visit to lead to opportunity to close one deal. And we put some numbers at the bottom that show the number of leads opportunities, close one deals and the resulting acquisition cost.

So if we take a top of the funnel strategy and you assume a 30 percent growth in the top of the funnel, the visit to lead conversion rate, and you make the big assumption of assuming that that 30 percent carries through to the entire funnel, which, by the way, is almost never the case. You get a significant improvement in close one deals and also a corresponding reduction in the acquisition costs.

But if we’re able to spread that improvement and actually improve the conversion rates down funnel from lead to opportunity as well as opportunity to deal, even if you do it in smaller amounts because you have less influence in that part of the funnel, you can see here that you get a much more significant improvement in revenue and a much more significant reduction in the acquisition costs.

So the point here is optimizing for the entire revenue funnel can generate significantly better incremental revenue than just focusing on top of the funnel. So don’t just think about it in terms of leads, think about it as optimizing the entire journey to revenue.

When we at funnel end we talk about revenue funnel optimization, this is our goal, optimize the entire customer journey to revenue.

So I want to leave you some takeaways here.

The first is that, of course, throwing money at paid channels is fast, and that’s why we do it. But it might not be very efficient, as we’ve seen today, and it could very well have diminishing returns over time.

The majority of your traffic is likely coming from direct or organic sources, and that also represents buyers at different stages. It’s not enough to just think about it as return traffic. You have buyers because your demand gen marketer coming at various different buying stages with differentiated intent.

And so if you’re able to optimize your website funnel across these buying stages, again, that’s what we call revenue funnel optimization, you can actually accelerate growth across every acquisition channel and have a much easier path to growth.

With that, I want to thank you for listening today, bye.

How Hotjar Can Help You Convert More Leads

Hotjar is a great complement to Google Analytics. Layering qualitative and visual data over the raw numbers gives you another dimension of insights.

But just like with your Google Analytics data, if you ignore key segments, you do so at your own risk.

Imagine, for example, that a heat map shows you that only 20 out of every 1,000 of visitors click on your Product Tour CTA. In fact, the scroll map shows you that only 15% of visitors even reach that section of the page.

You might conclude that the section and CTA don’t matter, and consider removing them.

Now imagine that all 20 of those visitors are leads – visitors who have identified themselves by signing up for a free trial, downloading a resource, or attending a webinar. Suppose that on average 15 of those 20 leads end up turning into opportunities. The Product Tour just went from wasted space to one of the highest-value interactions on the site!

Fortunately, it just takes a bit of work to begin segmenting your most valuable visitor data in Hotjar. Let’s look at how to do this with leads.

Why leads?

While leads might not be your most important identifiable visitor segment, for most B2B SaaS sites they deserve special attention. In fact, they’re already getting special treatment in your nurture campaigns. (Right?) And hopefully you’re personalizing offers and CTAs for them as well.

Still, the steps below will work for any segment you can identify. Target accounts, industry of interest, or existing customers can all be given VIP status in Hotjar.

Setup

Before you begin, make sure you have two things in place.

1. Hotjar Plus or Business

The free plan doesn’t support custom tags and triggers.

2. A way to identify leads on your website

Not sure how to do that? This post will walk you through it. And if you’re using Marketo, FunnelEnvy automatically syncs lead status with all your frontend tools – Google Analytics, Drift, Google Optimize, and yes, Hotjar.

Tag session recordings

Watching playback of visitor sessions is a great way to put yourself in your customer’s shoes. It’s also dauntingly time consuming. One day’s worth of recordings could take a month to view.

So clearly you need to prioritize what you focus on. Watching a half dozen leads interact with your website will yield more insight than watching a hundred anonymous visitors land, scroll, and bounce.

All you need to do is execute a single line of code when you identify a lead on the site:

hj('tagRecording', ['leads']);

Set this up, and you’ll be able to filter recordings later.

Screenshot of Hotjar recordings filtered for leads

(See the Hotjar docs for more detail on how this works.)

Trigger heat maps

Instead of mixing clicks from anonymous visitors, customers, and leads all into a single heat map, you can create one for leads only.

You’ll need to create a heat map with a JavaScript trigger, then fire the trigger when leads visit the page in question.

If you’re using FunnelEnvy for Marketo, it’s as easy as adding a Trigger to Google Tag Manager:

Screenshot of a Trigger in Google Tag Manager

(FunnelEnvy for Marketo can push visitor stage to the Data Layer, meaning you can use it to trigger any Tag)

Then create a Custom HTML Tag to fire the Hotjar code:

Screenshot of a Custom HTML Tag in Google Tag Manager

Create a custom poll for leads only

What page has the highest exit rate? What page do visitors spend the most time on? What are they looking for, and not finding?

The answer is probably different for leads compared with anonymous visitors. The only way to find out is to ask.

Lucky for you, you can trigger a custom poll with the same code that triggers custom heat maps.

So if you’ve added the Google Tag Manager logic shown above, all you have do to is create a poll with a JavaScript trigger. And you’re done!

Screenshot of a Hotjar poll

Ask every visitor this question, get a lot of noise. Ask leads only, find out what matters

Where to start

There’s a lot you can do to better understand (and more effectively convert) leads on your website. As a first step, just tag and watch some session recordings to see how leads navigate your site.

This requires a way to identify those leads in the first place. Solve that problem once, though, and you open up deeper insights in Google Analytics, custom playbooks in Drift, and personalization options in Google Optimize.

If you’re using Marketo, FunnelEnvy solves this for you. No need to bring in the dev team and turn it into a multi-month project. If you’re ready to start giving leads the special treatment they deserve, just get in touch.

By |2020-08-03T11:54:09-07:00July 13th, 2020|Analytics, Strategy, SaaS, B2B|0 Comments

Identify, Track, and Serve Custom Experiences to Leads

You’ve decided to improve on your one-size-fits-all website content by serving personalized content to leads. You figure that a free trial user will literally never click “Start Free Trial” … but they very well might click “Buy Now.” Especially if you give them clear reasons to do so.

Great! So, how will you target these visitors?

It’s a straightforward process of identifying “leads only” behavior, then ensuring you’re able to activate this data on your site.

What do leads do?

The answer is unique to your product, but it’s not a trick question.

Here are visitor behaviors you can use to identify leads:

  • Sign up for a trial
  • Opt in for a lead magnet
  • Click through on an email message sent to leads only
  • Trigger a domain or company match to an account that’s in the pipeline
  • Click “Log In” on the homepage

If you’re only looking to segment out leads in your analytics reporting, this might give you everything you need.

Your “Leads” segment is the set of all visitors who carried out any of the above actions. Even if you’re not tracking “Log In” clicks or using a firmographic data provider, you’ve got pageviews on /app, or /dashboard, or /whitepaper-download-thank-you. That’s enough to define a segment.

But to take the next logical step of serving a more relevant experience to these visitors, you’ll have to have this data available not just in your reports, but on the frontend of your website.

How to activate experiences for leads

Once you’ve narrowed down the list of  actions that define “leads only ” behavior on your site, you’ll need to attach some sort of identifiable metadata to the user across your website.

If you can spare a few developer cycles, setting a first-party cookie is a good option. Whenever a visitor starts a trial, or signs up for a webinar, set a cookie you can use to identify that they’re a lead. All your dev needs to know is the exact trigger (or triggers), the name and value you want to use for the cookie, and when it should expire.

Once this cookie is set in the visitor’s browser, you can use it to activate personalization campaigns, experiments, customized lead magnet offers, and whatever else you think might get leads to convert.

First party cookie targeting with Google Optimize

If you’re using Marketo, you already have a source of truth for a visitor’s status in the sales process, along with useful metadata about their site behavior, lead score, and more. All packaged up into a cookie that’s already on your site.

In that case, the easiest path forward is to use FunnelEnvy for Marketo to activate this data, which you can then integrate with Google Analytics, Google Optimize, Optimizely, Drift, and whatever else you’re using. No custom code required.

What to do next

You can start scoping this project right now. Write down the actions that identify visitors as leads in your pipeline. Forward this along to your dev team, and ask them what it will entail to set a custom cookie for visitors who complete these actions.

Or skip the back-and-forth by signing up for FunnelEnvy for Marketo. We’ll solve analytics, targeting, and activation. You can move on to designing a higher-converting experience,

By |2020-07-08T10:41:56-07:00July 7th, 2020|Digital Marketing, Analytics, B2B|0 Comments

Minimum Viable Personalization for Leads

Your website receives visitors in different stages of the buying process, who have varying needs and priorities. You recognize this, so you’ve installed a personalization platform. Where to begin?

First, a word on what not to do. Do not get click-and-drag happy with your platform’s audience tool, and end up creating a monstrosity like “Returning visitors from Texas using Firefox on Mobile.”

Complex audience targeting rules, X'd out

These audiences are easy to target, but hard to reason about, painful to maintain, and impossible to extract value from.

Instead, start with leads.

Why leads? (And what’s a lead?)

The exact definition will depend on your customer journey, but broadly speaking a lead is any visitor who has identified themself on your website.

This might include:

  • Free trial users
  • Whitepaper downloaders
  • Webinar attendees

Put another way, leads are visitors who are neither paying customers nor anonymous.

As for why you should provide a personalized experience for them, there are three main reasons:

  1. You can. They’ve signed up, so you know something about them.
  2. They’re your second-most-valuable visitor segment. (Customers are #1, but that’s a topic for another day.)
  3. Your current website is probably dominated by top of funnel content that they’ve already seen, and no longer find valuable.

Given how important this group is, it makes sense to provide an experience that’s relevant to them. But how do you do that without rewriting your whole website?

Where to personalize

Meet your leads where they’re already spending time. Finding out the answer to this question is as simple as segmenting your analytics data by leads, then looking at top pages.

The answer is probably “the Homepage and the Pricing page” but don’t take my word for it. Let the data tell you where to focus, and what kind of reach you can achieve.

Google Analytics screenshot of top pages visited by Leads

Once you’ve identified the top pages visited by leads, you can further prioritize by focusing on the elements they see and interact with.

For example, Hotjar allows you to trigger heat and scroll maps with custom code. That means you can create a “Leads only” heat map of your home page. (If that’s too hard, just keep your focus above the fold.)

How to personalize

This step is where the magic happens. What unique questions do leads on your website have? What tasks do they prioritize? What does activation look like?

To help structure your ideas, look for chances to do three things: Educate, remove friction, and nudge.

Educate

Does your homepage hero heading tout your product’s core value proposition? That’s great, but your leads probably know it by now. Can you change it to outline an important differentiator?

Does the homepage hero CTA still say “Free Trial”? You definitely don’t need that. Does it make sense to link to your knowledge base, or a quick start guide?

Remove friction

A simple improvement you can make is to show your free trial leads a more prominent “Log in” or “Visit My Dashboard” button. There’s a good chance that’s what they came to click.

You can also disable widgets and popups focused on lead generation. Those elements, by definition, can’t provide you with a new lead in this context. All they can do is annoy an existing lead.

Nudge forward

What steps does a visitor have to take before obtaining value from your product? Configure an integration, view a dashboard, import contacts?

When they were new to the site, pushing them toward this would’ve been overwhelming. Now that they’re more familiar with your product, though, they need this guidance.

Does your chat widget still ask “New here? Got any questions?” Why not start an onboarding-related conversation instead? A simple script along the lines of “Have you imported your contacts yet?” can transform this chatbot from a nuisance to a touch point for upgrades.

Stuck for ideas? Here are a couple of suggestions for websites we at FunnelEnvy know and love.

 

What you can do today

The first step toward obtaining value from a personalization strategy is convincing yourself that it’s worth the effort. So, start there.

What is the single highest-traffic page for existing leads? How many visitors does it get each month?

What’s the single most impactful element on that page? If you’re not sure, start with the hero heading copy and CTA.

What’s the current experience for leads? Is it relevant at all? Can you think of a message that would easily be 10 times more helpful?

If so, you’re onto something.

The good news is that the technical hurdles involved in making this change are solvable in any number of ways.

Your personalization tool might support targeting based on past visits to the /dashboard page. You might convince a friendly dev to set a cookie for new signups. If you use Marketo, FunnelEnvy lets you target by Smart List.

So take your newly acquired vision for a better lead experience, share it with the team. You’ll be hard pressed to find someone willing to fight to keep redundant CTAs on the page. I doubt anyone will argue that converting leads to sales is a wasted effort.

Starting personalization with a well-defined, high value, high reach, and observably different audience segment will make the difference between real ROI and a cringe-inducing vanity metrics report. So let’s go nurture some leads!

By |2020-07-10T09:40:07-07:00July 2nd, 2020|Analytics, SaaS, B2B|0 Comments
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